Intel also reaffirmed its plan to introduce a discrete graphics processor by 2020.
“One API” Software: Intel announced the “One API” project to simplify the programming of diverse computing engines across CPU, GPU, FPGA, AI and other accelerators. The project includes a comprehensive and unified portfolio of developer tools for mapping software to the hardware that can best accelerate the code. A public project release is expected to be available in 2019.
Memory and Storage: Intel discussed updates on Intel® Optane™ technology and the products based upon that technology. Intel® Optane™ DC persistent memory is a new product that converges memory-like performance with the data persistence and large capacity of storage. The revolutionary technology brings more data closer to the CPU for faster processing of bigger data sets like those used in AI and large databases. Its large capacity and data persistence reduces the need to make time-consuming trips to storage, which can improve workload performance. Intel Optane DC persistent memory delivers cache line (64B) reads to the CPU. On average, the average idle read latency with Optane persistent memory is expected to be about 350 nanoseconds when applications direct the read operation to Optane persistent memory, or when the requested data is not cached in DRAM. For scale, an Optane DC SSD has an average idle read latency of about 10,000 nanoseconds (10 microseconds), a remarkable improvement.2 In cases where requested data is in DRAM, either cached by the CPU’s memory controller or directed by the application, memory sub-system responsiveness is expected to be identical to DRAM (<100 nanoseconds).
The company also showed how SSDs based on Intel’s 1 Terabit QLC NAND die move more bulk data from HDDs to SSDs, allowing faster access to that data.
The combination of Intel Optane SSDs with QLC NAND SSDs will enable lower latency access to data used most frequently. Taken together, these platform and memory advances complete the memory and storage hierarchy providing the right set of choices for systems and applications.
Deep Learning Reference Stack: Intel is releasing the Deep Learning Reference Stack, an integrated, highly-performant open source stack optimized for Intel® Xeon® Scalable platforms. This open source community release is part of our effort to ensure AI developers have easy access to all of the features and functionality of the Intel platforms. The Deep Learning Reference Stack is highly-tuned and built for cloud native environments. With this release, Intel is enabling developers to quickly prototype by reducing the complexity associated with integrating multiple software components, while still giving users the flexibility to customize their solutions.
- Operating System: Clear Linux* OS is customizable to individual development needs, tuned for Intel platforms and specific use cases like deep learning;
- Orchestration: Kubernetes* manages and orchestrates containerized applications for multi-node clusters with Intel platform awareness;
- Containers: Docker* containers and Kata* containers utilize Intel® Virtualization Technology to help secure container;
- Libraries: Intel® Math Kernel Library for Deep Neural Networks (MKL DNN) is Intel’s highly optimized math library for mathematical function performance;
- Runtimes: Python* providing application and service execution runtime support is highly tuned and optimized for Intel architecture;
- Frameworks: TensorFlow* is a leading deep learning and machine learning framework;
- Deployment: KubeFlow* is an open-source industry-driven deployment tool that provides a fast experience on Intel architecture, ease of installation and simple use.
About Intel
Intel (NASDAQ: INTC), a leader in the semiconductor industry, is shaping the data-centric future with computing and communications technology that is the foundation of the world’s innovations. The company’s engineering expertise is helping address the world’s greatest challenges as well as helping secure, power and connect billions of devices and the infrastructure of the smart, connected world – from the cloud to the network to the edge and everything in between. Find more information about Intel at newsroom.intel.com and intel.com.
1Intel calculated 2022 total addressable market opportunity derived from industry analyst reports and internal estimates.
2Average idle read latency is the mean time for read data to return to a requesting processor. This is an average; some latencies will be longer. Tests document performance of components on a particular test, in specific systems. Differences in hardware, software or configuration will affect actual performance. Consult other sources of information to evaluate performance as you consider your purchase. For more complete information about performance and benchmark results, visit www.intel.com/benchmarks.
Forward-Looking Statements
